Arguments

sites

a data frame consisting of two variables: the first variable is
site IDs, and the second variable is a logical vector indicating which
sites to use in the analysis. The default is NULL.

subpop

a data frame describing sets of populations and subpopulations
for which estimates will be calculated. The first variable is site
IDs. Each subsequent variable identifies a Type of population, where
the variable name is used to identify Type. A Type variable
identifies each site with one of the subpopulations of that Type. The
default is NULL.

design

a data frame consisting of design variables. Variables should
be named as follows:
siteID = site IDs
wgt = final adjusted weights, which are either the weights for a
single-stage sample or the stage two weights for a two-stage sample
xcoord = x-coordinates for location, which are either the x-coordinates
for a single-stage sample or the stage two x-coordinates for a
two-stage sample
ycoord = y-coordinates for location, which are either the y-coordinates
for a single-stage sample or the stage two y-coordinates for a
two-stage sample
stratum = the stratum codes
cluster = the stage one sampling unit (primary sampling unit or cluster)
codes
wgt1 = final adjusted stage one weights
xcoord1 = the stage one x-coordinates for location
ycoord1 = the stage one y-coordinates for location
support = support values - the value one (1) for a site from a
finite resource or the measure of the sampling unit associated
with a site from an extensive resource, which is required for
calculation of finite and continuous population correction
factors
swgt = size-weights, which is the stage two size-weight for a two-
stage sample
swgt1 = stage one size-weights

data.ar

data frame of categorical response and stressor variables,
where each variable consists of two categories. If response or stressor
variables include more than two categories, occurrences of those categories
must be removed or replaced with missing values. The first column of this
argument is site IDs. Subsequent columns are response and stressor
variables. Missing data (NA) is allowed.

response.var

character vector providing names of columns in argument
data.ar that contain a response variable, where names may be repeated. Each
name in this argument is matched with the corresponding value in the
stressor.var argument.

stressor.var

character vector providing names of columns in argument
data.ar that contain a stressor variable, where names may be repeated. Each
name in this argument is matched with the corresponding value in the
response.var argument. This argument must be the same length as argument
response.var.

response.levels

list providing the category values (levels) for each
element in the response.var argument. This argument must be the same length
as argument response.var. The default is a list containing the values
"Poor" and "Good" for the first and second levels, respectively, of each
element in the response.var argument.

stressor.levels

list providing the category values (levels) for each
element in the stressor.var argument. This argument must be the same length
as argument response.var. The default is a list containing the values
"Poor" and "Good" for the first and second levels, respectively, of each
element in the stressor.var argument.

popcorrect

a logical value that indicates whether finite or continuous
population correction factors should be employed during variance
estimation, where TRUE = use the correction factor and FALSE = do not
use the correction factor. The default is FALSE. To employ the correction
factor for a single-stage sample, values must be supplied for argument
pcfsize and for the support variable of the design argument. To employ the
correction factor for a two-stage sample, values must be supplied for
arguments N.cluster and stage1size, and for the support variable of the
design argument.

pcfsize

size of the resource, which is required for calculation of
finite and continuous population correction factors for a single-stage
sample. For a stratified sample this argument must be a vector containing a
value for each stratum and must have the names attribute set to identify the
stratum codes. The default is NULL.

N.cluster

the number of stage one sampling units in the resource, which
is required for calculation of finite and continuous population
correction factors for a two-stage sample. For a stratified sample
this variable must be a vector containing a value for each stratum and
must have the names attribute set to identify the stratum codes. The
default is NULL.

stage1size

size of the stage one sampling units of a two-stage sample,
which is required for calculation of finite and continuous population
correction factors for a two-stage sample and must have the names
attribute set to identify the stage one sampling unit codes. For a
stratified sample, the names attribute must be set to identify both
stratum codes and stage one sampling unit codes using a convention where
the two codes are separated by the & symbol, e.g., "Stratum 1&Cluster 1".
The default is NULL.

sizeweight

a logical value that indicates whether size-weights should
be used in the analysis, where TRUE = use the size-weights and FALSE =
do not use the size-weights. The default is FALSE.

vartype

the choice of variance estimator, where "Local" = local mean
estimator and "SRS" = SRS estimator. The default is "Local".

conf

the confidence level. The default is 95%.

Value

Value is a data frame of attributable risk estimates for all combinations of
population Types, subpopulations within Types, and response variables.
Standard error and confidence interval estimates also are provided.